Vehicle overspeed prompting method based on overspeed tendency

Abstract

The invention relates to a vehicle overspeed prompting method based on overspeed tendency, which applies time sequence vehicle track characteristic data to realize overspeed tendency analysis of a driver under a gradual variable speed limit condition, and provides targeted speed limit measures for different types of drivers tending to overspeed and low-speed driving. The problem that traditional traffic variable speed limit control cannot perform targeted speed limit according to driving behavior characteristics of a driver and the problem that current expressway variable speed limit control lacks an optimization mechanism for an individual driver so that the driver compliance degree is not high are solved. Meanwhile, the early warning problem that the running speed of some vehicles on the expressway with the too high passenger-cargo ratio is too low is solved, a higher-acceptability and finer early warning mode can be provided for the vehicles running at the overspeed and the low speed in advance, a customized and personalized driving behavior early warning scheme is provided for the vehicles, the road speed discreteness is reduced, the traffic safety level is improved, and the driving safety is improved. The method has the characteristics of replicable popularization and strong robustness.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent traffic control, and particularly relates to a vehicle speeding prompt method based on speeding tendency. Background Art

[0002] With the development of sensing technology, artificial intelligence, 5G, and Internet of Things technology, the technology of precise and personalized vehicle instruction push has gradually accelerated towards practical application, and the technology of intelligent connected vehicles has been continuously updated and iterated. Intelligent connected vehicles will reconstruct the relationship among people, vehicles, and roads, enabling the perception and control of vehicles to reach a new level. With the popularization of motor vehicles and the growth of transportation demand, the current static speed control method adopted by highway safety proactive control technology and the information release method based on variable message signs can gradually no longer meet the needs of the intelligent connected environment. Firstly, the means of information release based on variable message signs cannot provide personalized speed limit guidance for specific vehicles, resulting in large differences in management effects among different individuals and having a negative impact on highway traffic safety. Secondly, due to the different layout intervals and speed values released by the continuously set variable speed limit signs on the highway, different drivers will adopt different driving behavior strategies under the influence of progressive lane-level variable speed limits, and targeted speed limit guidance needs to be carried out according to the driving behaviors of different drivers.

[0003] Due to differences in aspects such as age, gender, personality, occupation, and driving experience among drivers, there are significant differences in the driving behavior characteristics among individuals. The speed response of drivers under different speed limit conditions is closely related to their driving styles. However, it is difficult to obtain driving style data of drivers through ex-ante means such as questionnaires. Therefore, it is difficult to apply personalized speed limit guidance methods for individual drivers on a wide range of highways. Summary of the Invention

[0004] Aiming at the problem that traditional traffic variable speed limit control cannot perform targeted speed limit according to the driving behavior characteristics of drivers, and the problem that the current highway variable speed limit control lacks an optimization mechanism for individual drivers, resulting in low driver compliance, the present invention provides a vehicle speeding prompt method based on speeding tendency. By using devices such as radars and cameras installed on a large number of highways that can obtain continuous vehicle trajectories, the full-domain time-series speed data of drivers is obtained, and the speeding tendency mode classification of drivers under progressive variable speed limits is realized, and targeted speed warnings are given to them.

[0005] Select a section of road with a large variation in vehicle driving speed; deploy stepped lane-level speed limit signs at certain intervals on the roadside to gradually limit the speed of vehicles; according to the preset control strategy, use the variable speed limit system to issue control commands for corresponding lane-level speed limit control, and adjust the speed limit value of the lane-level variable speed limit board; use the vehicle trajectory data acquisition device to collect and analyze vehicle trajectory characteristic parameters, extract the vehicle trajectory characteristic data of the driver under different speed limit conditions, and construct a driver global speeding tendency model under progressive variable speed limit based on vehicle driving trajectory data; cluster the driver speeding tendency into three categories: high, medium, and low based on the driver global speeding tendency model under progressive variable speed limit; count the vehicle time-series speed, integrate the time for the speeding part above the maximum speed limit standard, and issue different types of speeding warning messages to the drivers with three types of speeding tendencies whose speeding part exceeds a certain threshold; count the vehicle time-series speed, integrate the time for the low-speed part below the minimum speed limit standard, and issue different types of low-speed warning messages to the drivers with three types of speeding tendencies whose low-speed part exceeds a certain threshold; realize vehicle-road communication by deploying RSU on the roadside and OBU on the vehicle end, and issue different speed limit warning prompt messages to drivers with different speeding tendencies. The vehicle speeding prompt system and method based on speeding tendency provided by the present invention apply time-series vehicle trajectory characteristic data, realize the analysis of the driver's speeding tendency under progressive variable speed limit conditions, provide targeted speed limit measures for different types of drivers prone to speeding and low-speed driving, solve the problem that traditional traffic variable speed limit control cannot carry out targeted speed limit according to the driver's driving behavior characteristics, and the problem that the current highway variable speed limit control lacks an optimization mechanism for individual drivers, resulting in low driver compliance. At the same time, it solves the warning problem of too low driving speeds of some vehicles on highways with too high passenger-cargo ratios, can provide a more acceptable and refined warning method for speeding and low-speed driving vehicles in advance, provide a customized and personalized driving behavior warning plan for them, reduce the road speed discreteness, improve the traffic safety level, and has the characteristics of being replicable, popularizable, and strong in robustness.

[0006] The object of the present invention is achieved through the following technical solutions:

[0007] 1) Select a section of road with a large variation in vehicle driving speed and deploy a series of lane-level variable speed limit information release devices at certain intervals;

[0008] 2) Deploy vehicle trajectory data acquisition devices at certain intervals in the road area to realize the collection and analysis of vehicle time-series trajectory data;

[0009] 3) According to the preset control strategy, use the variable information system to issue control commands for corresponding lane-level speed limit control, adjust the speed limit value of the lane-level variable speed limit board, and export the vehicle trajectory data and lane-level speed limit information release data in real time;

[0010] The lane-level variable speed limit board is an information instruction release device for the lane-level variable speed limit control system. It is installed on the gantry at an interval of 750 m. Each lane-level variable speed limit board issues variable speed limit information for one lane, and the variable speed limit instructions on different lanes and upstream and downstream can have different speed limit values;

[0011] 4) Use the vehicle trajectory data acquisition device to collect and analyze vehicle trajectory characteristic parameters, extract the vehicle trajectory characteristic data of the driver under different speed limit conditions, construct a progressive variable speed limit driver global speeding tendency model based on vehicle driving trajectory data, and use the MiniBatch K-Means clustering algorithm to cluster the driver's speeding tendency into 3 categories: high, medium, and low;

[0012] Preferably, in step 4), unify the length of the vehicle time-series trajectory data and the coordinate distribution of the acquisition points. Since the radar acquisition frequency is fixed, vehicles with different speeds take different lengths of time to pass through the same section, resulting in different lengths of vehicle speed time-series data. In order to achieve matching based on vehicle position during the clustering process of different time series, the vehicle speed time-series data of each vehicle is interpolated at an interval of 1 m with the longitudinal position as the "time series", and the vehicle speed time-series data of each vehicle is processed into equal-length time-series data.

[0013] Preferably, in step 4), initialize the clustering center: randomly select K time series from the data set as the initial clustering centers. These series will become the representative shapes of the clustering. Set the number of clusters to 3.

[0014] Preferably, in step 4), distance metric: use the distance metric to calculate the distance between each time series and each clustering center.

[0015] Preferably, in step 4), assign data points: assign each time series to the cluster where the nearest clustering center is located. In this way, each series will be classified into the cluster with the nearest distance to it.

[0016] Preferably, in step 4), update the clustering center: update the clustering center using the average value of the time series assigned to each cluster.

[0017] Preferably, in step 4), repeat the iteration: repeat the above steps until the clustering center no longer changes and reaches the predetermined number of iterations.

[0018] 5) Statistically analyze the vehicle time-series speed, integrate the time for the speeding part above the highest speed limit value standard, and issue different types of speeding warning information to the three types of drivers with speeding tendencies whose speeding parts exceed a certain threshold;

[0019] Preferably, in step 5), the sequential speed of each vehicle and the sequential variable speed limit value of the lane to which it belongs are statistically calculated;

[0020] Preferably, in step 5), the time is integrated for the overspeed part above the maximum speed limit value standard;

[0021] Preferably, in step 5), for drivers with different overspeed tendencies, when the integral value of the overspeed part over time exceeds a specific threshold, a red alert is issued to the driver;

[0022] 6) Statistically calculate the sequential speed of the vehicle, integrate the time for the low-speed part below the minimum speed limit value standard, and issue different types of low-speed warning messages to three types of drivers with different overspeed tendencies whose low-speed parts exceed a certain threshold;

[0023] Preferably, in step 6), the sequential speed of each vehicle and the sequential variable speed limit value of the lane to which it belongs are statistically calculated;

[0024] Preferably, in step 6), the time is integrated for the low-speed part above the maximum speed limit value standard;

[0025] Preferably, in step 6), for drivers with different overspeed tendencies, when the integral value of the low-speed part over time exceeds a specific threshold, a red alert is issued to the driver;

[0026] 7) Vehicle-road communication is realized by deploying RSU on the roadside and OBU on the vehicle end, and different speed limit warning prompt messages are issued to drivers with different overspeed tendencies.

[0027] A vehicle overspeed prompt method based on overspeed tendency provided by the present invention, compared with the prior art, at least includes the following

[0028] Beneficial effects:

[0029] 1) The vehicle overspeed prompt system and method based on overspeed tendency provided by the present invention apply the sequential vehicle trajectory characteristic data, realize the overspeed tendency analysis of drivers under the condition of progressive variable speed limit, provide targeted speed limit measures for different types of drivers who tend to overspeed and drive at low speed, solve the problem that the traditional traffic variable speed limit control cannot carry out targeted speed limit according to the driving behavior characteristics of drivers, and the problem that the current highway variable speed limit control lacks an optimization mechanism for individual drivers, resulting in low driver compliance.

[0030] 2) The present invention proposes corresponding speed over - speed and low - speed warning algorithms for high - speed and low - speed vehicles. At the same time, it solves the warning problem of too low driving speeds of some vehicles on highways with too high passenger - to - cargo ratios. It can provide a more acceptable and refined warning method for over - speed and low - speed vehicles in advance, provide a customized and personalized driving behavior warning plan for them, reduce road speed discreteness, and improve traffic safety level. It has the characteristics of being replicable, popularizable, and having strong robustness. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a schematic diagram of the principle of the vehicle over - speed prompting method based on over - speed tendency in the embodiment.

[0032] Figure 2 It is a schematic diagram of the layout method of variable speed limit information release devices in the vehicle over - speed prompting method based on over - speed tendency in the embodiment.

[0033] Figure 3 It is a schematic diagram of the layout method of traffic flow parameter collection devices in the vehicle over - speed prompting method based on over - speed tendency in the embodiment.

[0034] Figure 4 It is a schematic diagram of the two - dimensional clustering results of three over - speed tendencies in the vehicle over - speed prompting method based on over - speed tendency in the embodiment.

[0035] Figure 5 It is a schematic diagram of the three - dimensional clustering results of three over - speed tendencies in the vehicle over - speed prompting method based on over - speed tendency in the embodiment.

[0036] Figure 6 It is a schematic diagram of the vehicle speed distributions of three over - speed tendencies in the vehicle over - speed prompting method based on over - speed tendency in the embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0037] The following further elaborates in detail on a vehicle over - speed prompting method based on over - speed tendency of the present invention with reference to the drawings and specific embodiments:

[0038] Embodiment:

[0039] A vehicle over - speed prompting method based on over - speed tendency includes the following steps:

[0040] 1) A series of lane - level variable speed limit information release devices are arranged at a certain interval on a section of road with large changes in vehicle driving speed.

[0041] The alignment of the road needs to comply with the requirements of the "Code for Highway Route Design" (JTG D20□2017); the setting of signs and markings in the scene needs to comply with the requirements of the "Road Traffic Signs and Markings" (GB 5768□2009) and the "Code for Design of Highway Speed Limit Signs" (JTG / T 3381□02□2020). The layout method is as Figure 2 shown.

[0042] 2) Vehicle trajectory data collection devices are arranged at certain intervals in the road area to achieve the collection and analysis of sub-meter-level sequential vehicle trajectories continuously without interruption.

[0043] The speed collection accuracy is not less than 1 km / h, the collection frequency reaches 10 Hz, and the layout method of the collection equipment is as Figure 3 shown.

[0044] 3) According to the preset control strategy, use the variable information system to issue and control corresponding lane-level speed limit control instructions, adjust the speed limit value of the lane-level variable speed limit board, and export the traffic flow parameters and lane-level speed limit information release data in real time.

[0045] The lane-level variable speed limit board is an information instruction release device of the variable speed limit control system, which is arranged on the gantry at an interval of 750 m. Each lane-level variable speed limit board issues variable speed limit information for one lane, and the lane-level speed limit instructions on different lanes and upstream and downstream can have different speed limit values. By changing the speed limit value of the variable speed limit sign in real time, the running state of the road traffic flow can be changed in real time.

[0046] 4) Use the vehicle trajectory data collection device to collect and analyze the vehicle trajectory characteristic parameters, extract the vehicle trajectory characteristic data of the driver under different speed limit conditions, construct a progressive variable speed limit driver's global speeding tendency model based on the vehicle driving trajectory data, and use the MiniBatch K-Means clustering algorithm to cluster the driver's speeding tendency into 3 categories: high, medium, and low:

[0047] Specifically, a global speeding tendency index based on the driver's multi-section speeding degree is constructed. The speeding degree values of each section relative to the lane speed limit at 50 meters downstream of each variable speed limit board are selected respectively to construct the lane-level continuous speed limit driver's global speeding tendency index. The calculation method of the speeding degree value of each section is as follows:

[0048]

[0049] Among them, C (i，j) is the speeding degree value of vehicle i downstream of the jth variable information board, Averagespeed (i，j) is the running speed of vehicle i at 200 m downstream of the jth variable information board, VSL (j)is the speed limit value of the j-th variable message sign.

[0050] Specifically, the length of the vehicle time-series trajectory data and the distribution of the collection point coordinates are unified. Since the radar acquisition frequency is fixed, vehicles with different speeds take different lengths of time to pass through the same section of the road, resulting in different lengths of vehicle speed time-series data. In order to achieve matching based on vehicle position during the clustering process of different time series, the speed time-series data of each vehicle uses the longitudinal position as the "time series" and is interpolated at intervals of 1 m to process the speed time-series data of each vehicle into equal-length time-series data.

[0051] Specifically, initialize the cluster centers: randomly select K time series from the dataset as the initial cluster centers. These series will become the representative shapes of the clusters. Set the number of clusters to 3.

[0052] Specifically, shape distance metric: use a distance metric to calculate the distance between each time series and each cluster center.

[0053] Specifically, assign data points: assign each time series to the cluster where the nearest cluster center is located. In this way, each series will be classified into the cluster with the closest distance to it.

[0054] Specifically, update the cluster centers: update the cluster centers using the average of the time series assigned to each cluster.

[0055] Specifically, repeat iteration: repeat the above steps until the cluster centers no longer change and reach a predetermined number of iterations.

[0056] Finally, obtain the speed clustering schematic diagrams of three types of speeding-prone drivers, as shown in Figure 4 and 5 shown. The comparison of the speed distributions of the three global speed trajectory patterns is shown in Figure 6 shown.

[0057] 5) Statistically analyze the vehicle time-series speed, integrate the time for the speeding part above the maximum speed limit value standard, and issue different types of speeding warning messages for the three types of speeding-prone drivers whose speeding parts exceed a certain threshold;

[0058] Specifically, statistically analyze the time-series speed of each vehicle and the variable speed limit value of the corresponding lane time series.

[0059] Specifically, integrate the time for the speeding part above the maximum speed limit value standard, and the calculation method is as follows:

[0060] O i (t) = ∫(Speed i (t) - VSL i (t))dt

[0061] Among them, O i (t) is the integral value of the overspeed part of vehicle i above the maximum speed limit standard at time t with respect to time, Speed i (t) is the running speed of vehicle i at time t, VSL i (t) is the speed limit value of the variable message sign in the lane where vehicle i is located at time t.

[0062] Specifically, for a driver with a high tendency to overspeed, when O i (t) exceeds , a red alert is issued to the driver. For a driver with a medium tendency to overspeed, when O i (t) exceeds , a red alert is issued to the driver. For a driver with a low tendency to overspeed, when O i (t) exceeds , a red alert is issued to the driver. The specific calculation method is as follows:

[0063]

[0064] 6) Statistically analyze the sequential speed of the vehicle, integrate the low-speed part below the minimum speed limit standard with respect to time, and issue different types of low-speed warning messages to three types of drivers with different overspeed tendencies whose low-speed parts exceed a certain threshold.

[0065] Specifically, statistically analyze the sequential speed of each vehicle and the sequential variable speed limit value of the lane to which it belongs.

[0066] Specifically, integrate the low-speed part above the minimum speed limit standard with respect to time. The calculation method is as follows:

[0067] L i (t) = ∫(LS i (t) - Speed i (t))dt

[0068] Among them, L i (t) is the integral value of the low-speed part of vehicle i above the minimum speed limit standard at time t with respect to time, Speed i (t) is the running speed of vehicle i at time t, LS i (t) is the minimum speed limit value of the lane where vehicle i is located at time t. If not available, it is replaced by 0.6 * VSL i (t).

[0069] Specifically, for a driver with a high tendency to overspeed, when L i (t) exceeds For a driver with a medium tendency to overspeed, when L i (t) exceeds For drivers with low speeding tendency, when L i (t) exceeds When the three conditions are met at the same time, all warning information will be cancelled. If the three conditions are not met at the same time, then when L i (t) exceeds When the speed limit is reached, a red alert is issued to the driver. For drivers with a medium tendency to speed, when O i (t) exceeds When the speed limit is reached, a red alert is issued to the driver. For drivers with a low tendency to speed, when O i (t) exceeds When the driver is at a red alert, the specific calculation method is as follows:

[0070]

[0071] 7) By deploying RSU on the roadside and OBU on the vehicle side to achieve vehicle-road communication, different speed limit warning messages are issued to drivers with different speeding tendencies.

[0072] The vehicle speeding warning system and method based on speeding tendency provided by the present invention realize the speeding tendency analysis of the driver under the condition of progressive variable speed limit, provide targeted speed limit measures for different types of drivers who tend to speed and underspeed, solve the problem that traditional traffic variable speed limit control cannot carry out targeted speed limit according to the driving behavior characteristics of the driver, and the problem that the current variable speed limit control of highways lacks an optimization mechanism for individual drivers, resulting in low driver compliance, and at the same time solves the early warning problem of too low speed of some vehicles on highways with too high passenger-to-cargo ratio, can provide a more acceptable and refined early warning method for speeding and underspeed vehicles in advance, provide them with a customized and personalized driving behavior early warning plan, reduce road speed discreteness, improve traffic safety level, and have the characteristics of replicability and strong robustness.

[0073] The examples of the present invention are described in detail above in conjunction with the embodiments, but the present invention is not limited to the above examples. Various changes can be made within the knowledge scope of ordinary technicians in the field without departing from the purpose of the present invention, and should also be regarded as the protection scope of the present invention.

Claims

1. A vehicle speeding warning method based on speeding tendency, characterized in that: The following steps are involved: 1) Select road sections with large changes in vehicle speed, and place stepped lane-level speed limit signs at certain intervals on the roadside to limit the speed of vehicles step by step; 2) Deploy vehicle trajectory data collection devices at a certain interval on the road area to collect and analyze vehicle time series trajectory data; 3) According to the preset control strategy, the variable information system is used to issue and control the corresponding lane-level speed limit control instructions, adjust the speed limit value of the lane-level variable speed limit plate, and export the vehicle trajectory data and lane-level speed limit information release data in real time; 4) The vehicle trajectory data acquisition device is used to collect and analyze the vehicle trajectory characteristic parameters, extract the vehicle trajectory characteristic data of the driver under different speed limit conditions, and build a driver's global speeding tendency model under a progressive variable speed limit based on the vehicle driving trajectory data. The driver's speeding tendency is clustered into three categories: high, medium, and low using the MiniBatch K-Means clustering algorithm; 5) Count the vehicle's sequential speed, integrate the time for the speeding portion on the maximum speed limit, and issue different types of speeding warning information to the three types of drivers with speeding tendencies whose speeding portion exceeds a certain threshold; 6) Count the vehicle's sequential speed, integrate the time in the low-speed part under the minimum speed limit standard, and issue different types of low-speed warning information to the three types of drivers with speeding tendencies whose low-speed part exceeds a certain threshold; 7) By deploying RSU on the roadside and OBU on the vehicle side to achieve vehicle-road communication, different speed limit warning messages are issued to drivers with different speeding tendencies.

2. The vehicle speeding warning method based on speeding tendency according to claim 1 is characterized in that: In step 2), radar and camera vehicle trajectory data acquisition devices are deployed at a certain interval on the road to obtain continuous and uninterrupted sub-meter time-series vehicle trajectories. The speed acquisition accuracy is not less than 1km / h, and the acquisition frequency reaches 10Hz, providing a data basis for the collection and analysis of the driver's real-time time-series driving behavior characteristics.

3. The vehicle speeding warning method based on speeding tendency according to claim 1 is characterized in that: In step 3), the vehicle time-series trajectory data and lane-level speed limit information release data are all collected in real time and use UTC time, and the location of data release uses a unified stake number coordinate.

4. The vehicle speeding warning method based on speeding tendency according to claim 1 is characterized in that: In step 4), the vehicle trajectory feature data of the driver under different speed limit conditions is extracted, and a global speeding tendency model of the driver under a progressive variable speed limit based on the vehicle driving trajectory data is constructed. The driver's speeding tendency is clustered into three categories: high, medium, and low using the MiniBatch K-Means clustering algorithm. The specific steps are as follows: a) A global speeding tendency index based on the driver's speeding degree in multiple sections was constructed. The speeding degree value of each section 50 meters downstream of each variable speed limit plate relative to the speed limit of the lane was selected to construct the driver's global speeding tendency index under lane-level continuous speed limit. The speeding degree value of each section was calculated as follows: Among them, C (i，j) is the speeding degree of vehicle i downstream of the jth variable information board, Averagespeed (i，j) is the running speed of vehicle i at 200 m downstream of the jth variable message board, VSL (j) is the speed limit value of the jth variable information board; b) Unify the length of vehicle time series trajectory data and the distribution of acquisition point coordinates: Since the radar acquisition frequency is fixed, vehicles with different speeds take different time to pass through the same road section, resulting in different lengths of speed time series data. In order to achieve matching based on vehicle position in the clustering process of different time series, the speed time series data of each vehicle uses the longitudinal position as the time series and interpolates at a spacing of 1m, processing the speed time series data of each vehicle into equal-length time series data; c) Initialize cluster centers: randomly select K time series from the data set as the initial cluster centers to become the representative shape of the cluster, and set the number of clusters to 3; d) Distance metric: Use the distance metric to calculate the distance between each time series and each cluster center; e) Assign data points: Assign each time series to the cluster with the closest cluster center. Each series will be classified into the cluster with the closest distance to it. f) Update cluster centers: Update cluster centers using the average value of the time series assigned to each cluster; g) Repeat iteration: Repeat the above steps until the cluster center no longer changes and reaches the predetermined number of iterations.

5. The vehicle speeding warning method based on speeding tendency according to claim 1 is characterized in that: In step 5), the vehicle sequential speed is counted, the time is integrated for the speeding part on the maximum speed limit value standard, and different types of speeding warning information are issued to the three types of drivers with speeding tendencies whose speeding part exceeds a certain threshold. The specific steps are as follows: a) Count the sequential speed of each vehicle and the sequential variable speed limit of its lane, b) The time for the speed exceeding the maximum speed limit is integrated and calculated as follows: O i (t)=∫(Speed i (t)-VSL i (t))dt Among them, O i (t) is the integral value of the speeding part of vehicle i over the maximum speed limit at time t over time, Speed i (t) is the running speed of vehicle i at time t, VSL i (t) is the speed limit value of the variable information board in the lane where vehicle i is located at time t; c) For drivers with a high tendency to speed, when O i (t) exceeds When the speed limit is reached, a red alert is issued to the driver. For drivers with a medium tendency to speed, when O i (t) exceeds When the speed limit is reached, a red alert is issued to the driver. For drivers with a low tendency to speed, when O i (t) exceeds When the red alert is issued to the driver, the specific calculation method is as follows:

6. The vehicle speeding warning method based on speeding tendency according to claim 1, characterized in that: In step 6), the vehicle sequential speed is counted, the time is integrated in the low-speed part under the minimum speed limit value standard, and different types of low-speed warning information are issued to the three types of drivers with speeding tendencies whose low-speed part exceeds a certain threshold. The specific steps are as follows: a) Count the sequential speed of each vehicle and the sequential variable speed limit of the lane to which it belongs; b) Integrate the time in the low speed portion of the minimum speed limit value standard, and the calculation method is as follows: L i (t)=∫(LS i (t)-Speed i (t))dt Among them, L i (t) is the integral value of the low speed portion of vehicle i at the minimum speed limit value standard at time t over time, Speed i (t) is the running speed of vehicle i at time t, LS i (t) is the minimum speed limit of the lane where vehicle i is located at time t. If it is not available, 0.6*VSL is used. i (t) substitution; c) For drivers with a high tendency to speed, when L i (t) exceeds For drivers with a medium tendency to speed, when L i (t) exceeds For drivers with low speeding tendency, when L i (t) exceeds When the three conditions are met at the same time, all warning information will be cancelled. If the three conditions are not met at the same time, then when L i (t) exceeds When the speed limit is reached, a red alert is issued to the driver. For drivers with a medium tendency to speed, when O i (t) exceeds When the speed limit is reached, a red alert is issued to the driver. For drivers with a low tendency to speed, when O i (t) exceeds When the red alert is issued to the driver, the specific calculation method is as follows:

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